A new integrated approach for engineering characteristic prioritization in quality function deployment

As a customer-driven quality improvement tool, quality function deployment (QFD) can convert customer requirements (CRs) into appropriate engineering characteristics (ECs) in product design and development. However, the conventional QFD method has been criticized for a variety of drawbacks, which limit its efficiency and potential applications. In this study, a new QFD approach integrating picture fuzzy linguistic sets (PFLSs) and the evaluation based on distance from average solution (EDAS) method is proposed for the determination of ranking order of ECs. The PFLSs are utilized to express the judgements of experts on the relationships among CRs and ECs. Then, the EDAS method is extended under picture fuzzy linguistic environment for the prioritization of the ECs identified in QFD. Moreover, a combined weighing method based on technique for order of preference by similarity to ideal solution (TOPSIS) and maximum entropy theory is established to calculate the weights of experts objectively. Finally, a product-service system design is provided to illustrate the effectiveness of the proposed QFD approach. The result shows that the manufacturer should pay more attention to “Meantime before failure”, “Warning feature” and “Quality of product manual”. Feedback from domain experts indicates that the integrated approach being proposed in this paper is more suitable for assessing and prioritizing ECs in QFD.     

Research on multi-objective decision-making under cloud platform based on quality function deployment and uncertain linguistic variables

With developments in cloud computing and big data, the term “cloud” has become a household name owing to its characteristics of smartness and connectedness. Cloud-based platforms are associated with people. However, multi-objective decision-making problem in cloud platforms has not been extensively studied. There is no consensus on the reasonable and effective implementation of the decision-making model to select the optimum design scheme in a cloud platform and its establishment to objectively evaluate its significance. In this study, to efficiently and accurately realize the optimal selection of design scheme, a fuzzy evaluation mechanism in handling the vagueness and uncertainty is established, with the advantage of quality function deployment and strength Pareto evolutionary algorithm in decision analysis. A case study is provided to validate the proposed approach in cloud platforms. To reveal the advantages of the proposed method, it was compared with other methods such as the requirement-scenario-experience evaluation framework and a rough number-based integrated method. MATLAB programming was used for this comparison and accuracy certification. The result shows that the proposed model is more efficient and dynamic and provided users with multidimensional evaluation based on open and distributed resources system.     

Fuzzy cognitive map based quality function deployment approach for dishwasher machine selection

The traditional quality function deployment (QFD) approach deals with the weights of customer requirements (CRs), relationships among CRs and design requirements (DRs), correlation among DRs by using crisp values. This paper uses fuzzy numbers to improve the drawbacks of the traditional QFD method because fuzzy numbers enable to make consistent decisions in uncertain environment to decision makers. The existing papers handle a simple multiplication operation to calculate the correlation among CRs and the correlation among DRs. This study proposes fuzzy cognitive map (FCM) approach to calculate these correlations so that FCM is a successful method to handle the interactions among criteria. This paper contributes to the literature by integrating QFD approach and fuzzy cognitive map approach. The weights of DRs are defined in the result of the proposed QFD approach. These weights are used to evaluate the dishwasher machine alternatives in intuitionistic fuzzy VIKOR method. Intuitionistic fuzzy number (IFS) ensures to handle more information than type-1 fuzzy number to describe the fuzziness and the uncertainty of the real life world. Finally, the proposed approach has been implemented to a dishwasher machine selection in order to test its validity.     

Fuzzy quality function deployment: determining the distributions of effort dedicated to technical change

A model is presented that develops the Quality Function Deployment (QFD) House of Quality tool into a fuzzy‐set based multi‐criteria decision‐making process to determine the distributions of effort directed toward technical changes. When customers are polled for desired product‐specific attributes, the responses are typically defined by linguistic variables that represent a fuzzy set distribution. Fuzzy sets also define customer perceptions of the product attributes and technical expert opinions about product design criteria relative to marketplace competitors. Therefore, for each technical criterion, the following factors have an effect on the decision to implement change(s): (1) fuzzy sets providing evidence of customer need for attributes; (2) motivation to change to satisfy desired customer attributes; (3) motivation for technical criterion change; and (4) the strength of the relationships between the attributes and the technical criterion. Priority rankings are linked to the distributions of effort to apply in fulfilling continuous product improvement.     

Managing software requirements using quality function deployment

In this article we describe and discuss QFD (quality function deployment) as a framework for managing software requirements. Experiences were gained while participating as researchers in a commercial large-scale software telecommunications project at Ericsson Radio Systems AB. We found that prerequisites for succeeding with QFD include having visible customers and users, forming a cross-functional team adequately trained in QFD, and allowing adequate time for its first application. Advantages of using QFD are: better focus on customers and users, an effective means of prioritizing and communicating software requirements; and managing non-functional requirements. Issues not fully supported by QFD include adequate abstractions levels in describing requirements, handling temporal relations between requirements and initiating the use of QFD for a new development project.     

Routine design with information content and fuzzy quality function deployment

Design can be classified into four basic categories: creative design, innovative design, redesign, and routine design. This paper describes a method for performing routine design by utilizing information content and fuzzy quality function deployment. An attempt has been made to associate with each critical characteristic of a product a value representing the information content, which is a measure of probability that a system can produce the parts as specified by the designer, using a specific manufacturing technology for making the parts. Once the information content of each design alternative is computed, the system will select an alternative with the minimum amount of information content. The proposed method provides us with a means for solving the critical design evaluation and validation problem.     

A quantitative approach for setting technical targets based on impact analysis in software quality function deployment (SQFD)

Target setting in software quality function deployment (SQFD) is very important since it is directly related to development of high quality products with high customer satisfaction. However target setting is usually done subjectively in practice, which is not scientific. Two quantitative approaches for setting target values: benchmarking and primitive linear regression have been developed and applied in the past to overcome this problem (Akao and Yoji, 1990). But these approaches cannot be used to assess the impact of unachieved targets on satisfaction of customers for customer requirements. In addition, both of them are based on linear regression and not very practical in many applications. In this paper, we present an innovative quantitative method of setting technical targets in SQFD to enable analysis of impact of unachieved target values on customer satisfaction. It is based on assessment of impact of technical attributes on satisfaction of customer requirements. In addition both linear and non linear regression techniques are utilized in our method, which certainly improves the existing quantitative methods which are based on only linear regression. Frank Liu is currently an associate professor and a director of the McDonnel Douglass Foundation software engineering laboratory in the University of Missouri-Rolla. He has been working on requirements engineering, software quality management, and knowledge based software engineering since 1992. He has published about 50 papers in peer-reviewed journals and conferences in the above areas and several other software engineering application areas. He participates in research projects with a total amount of funds of more than four millions dollars as a PI or Co-PI sponsored by the National Science Foundation, Sandia National Laboratory, U.S. Air Force, University of Missouri Research Board, and Toshiba Corporation. He has served as a program committee member for many conferences. He was a program committee vice chair for the 2000 International Conference on Software Engineering and Knowledge Engineering. Kunio Noguchi is a senior quality expert in the software engineering center in the Toshiba Corporation. He has published several papers in the area of quality management systems. Anuj Dhungana was a M.S. graduate student in the computer science department at the Texas Tech University when he performed this research. V.V.N.S.N. Srirangam A. was a M.S. graduate student in the computer science department at the Texas Tech University when he performed this research. Praveen Inuganti was a M.S. graduate student in the computer science department at the University of Missouri-Rolla when he performed this research.     

Quality function deployment implementation based on Fuzzy Kano model: An application in PLM system

Product lifecycle management (PLM), a strategic business system allows more effective communication among different groups at dispersed locations to share ideas and access information needed for developing new products and executing innovative processes. The main function of PLM is to develop an attractive system which ensures customer satisfaction. Therefore, one of the important topics of the PLM system developments is to take customer requirements into consideration. Quality function deployment (QFD) has been widely used for numerous years; it is one of the structured methodologies that are used to translate customer needs into specific quality development. However, in the traditional QFD approach, each element’s interdependence and customer requirements are usually not systematically treated. Additionally, the Kano model can effectively classify customer demand attributes, but to make Kano model more objective in the course of weighing, we have also included Fuzzy mode in our discussion. This study presents an integrative approach by incorporating the Kano model with Fuzzy mode into the matrix of QFD and adjusting customer requirement weights. This approach can fulfill two objectives, First, through the Kano model with the Fuzzy mode, it will not only discriminate out options for the required attributes in much more breadth but also simultaneously render the discretions on the linguistic implications much more accurate with the aid of the ambiguous questionnaire response method. Second, combining the Kano model and QFD, can not only provide a new way to optimize the product design but can also enhance customer satisfaction and loyalty, and minimize dissatisfaction. The proposed methods can be useful to both practitioners and researchers. To illustrate our findings, we have incorporated an example which suggests that the proposed approach can contribute to the creation of attractive PLM attributes and PLM innovation.     

基于品质功能展开的产品优化设计

研究品质功能展开（QFD）的产品优化设计问题，考虑产品设计过程中的设计预算，通过引进计划可达水平，实际可达水平等概念，提出了产品优化设计的用户总体满意模型，该方法综合考虑了设计预算和各设计属性的实际可达水平需求以及各设计属性之间的相关性作用，更能反映设计过程的实际情况。     

Distance measure for Fermatean fuzzy linguistic term sets based on linguistic scale function: An illustration of the TODIM and TOPSIS methods

In this paper, we propose the Fermatean fuzzy linguistic term set (FFLTS) based on the linguistic scale function. A new similarity measure between FFLTSs is constructed, which not only includes the linguistic scale function but also combines the cosine similarity measure and Euclidean distance measure, and then the related properties of the similarity measure are proven. A corresponding distance measure is obtained according to the relationship between the distance measure and similarity measure. Furthermore, we extend the Tomada de Decisão Interativa Multicritério (TODIM) method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to the corresponding distance measure under the Fermatean fuzzy linguistic environment. The main advantages of the proposed methods are that they can not only transform linguistic information effectively in different decision environments but also improve the adaptability of FFLTS in decision-making problems. Finally, a numerical example is provided to illustrate the effectiveness and feasibility of the proposed methods, which are also compared with other existing methods. The sensitivity analysis of the parameters and the influence of linguistic scale function on the ranking results are also discussed.     

Multiattribute decision making based on power operators for linguistic intuitionistic fuzzy set using set pair analysis

The aim of the presented paper is to give a multiattribute decision making (MADM) method under the linguistic intuitionistic fuzzy (LIF) environment using the set pair analysis (SPA) theory. LIF set can express the qualitative information in terms of linguistic variables, whereas the connection number (CN) based on the “identity,” “discrepancy,” and “contrary” degrees of the SPA theory handles the uncertainties and certainties systems. On the basis of these features, we develop some series of linguistic CN (LCN) power weighted and ordered weighted geometric aggregation operator to aggregate the different LCNs. Several properties of the operators are also studied. Afterward, we present a novel MADM method to solve decision‐making problems under LIF set environment and illustrate with several examples to validate it. A comparative analysis is also presented to show the results.     

Using Cpk index with fuzzy numbers to evaluate service quality

Service quality is measured by customers' satisfaction. Traditionally, the degree of satisfaction is calculated from the data obtained from questionnaires that have been filled by customers directly. The percentile of each different level of a customer's satisfaction is employed to summarize and compare the quality of service provided by different enterprises. This approach does not consider the consistency of the customers' perceptions, thus making comparison difficult. This paper introduces the concept of a process capability index that considers both the average and the consistency of the data simultaneously. Evaluations of service quality are usually vague and linguistic. We use the fuzzy numbers of linguistic variables developed in fuzzy set theory to modify the process capability index, and then apply it to evaluate the quality of a service. The average and consistency of the data obtained from a service quality evaluation are thus considered simultaneously, making the comparison of the performance of service quality easier. Moreover, the value of the index can be applied to help to point out the direction for improving the performance of service quality whenever it is lower than some default value.     

Construction of house of quality for new product planning: A 2-tuple fuzzy linguistic approach

A house of quality (HOQ) diagram is used to analyze the critical factors involved in the quality function deployment (QFD) processes for the new product planning (NPP). The principal tasks of the QFD acting process comprise describing and scoring customer requirements (CRs); determining design requirements (DRs), the relationship between CRs and DRs, the correlations among CRs, and the correlations among DRs. Finally, the DRs can be scored by these assessments in NPP. This study proposes various methods of scoring the requirements of current and potential customers to reflect the knowledge and preference differences among different customers regarding CRs. The CR scores provided by different customers can be assessed by using linguistic, numerical, and interval values, or can be assessed using linguistic label sets with different granularity. A 2-tuple fuzzy linguistic computational approach is adopted to aggregate the CR importance scores obtained from customers by using various methods. In addition, to accurately rate the DRs, a modified relationship between CRs and DRs is proposed. The proposed HOQ construction model is practical because it prevents the loss of information during the QFD process for NPP. An example is used to demonstrate the applicability of the proposed model.     

Multi-attribute group decision-making methods based on q-rung orthopair fuzzy linguistic sets

With the continuous development of the economy and society, decision-making problems and decision-making scenarios have become more complex. The q-rung orthopair fuzzy set is getting more and more attention from researchers, which is more general and flexible than Pythagorean fuzzy set and intuitionistic fuzzy set under complex vague environment. In this study, the concept of q-rung orthopair fuzzy linguistic set (q-ROFLS) is proposed and a new q-rung orthopair fuzzy linguistic method is developed to handle MAGDM problem. Firstly, the conception, operation laws, comparison methods, and distance measure methods of the q-ROFLS are proposed. Secondly, the q-ROFL weighted average operator, q-ROFL ordered weighted average operator, q-ROFL hybrid weighted average operator, q-ROFL weighted geometric operator, q-ROFL ordered weighted geometric operator, and q-ROFL hybrid weighted geometric operator are proposed, and some interesting properties, special cases of these operators are investigated. Furthermore, a new method to cope with MAGDM problem based on q-ROFL weighted average operator (q-ROFL weighted geometric operator) is developed. Finally, a practical example for suppliers selection is provided to verify the practicality of the presented method, and the effectiveness and flexibility of the presented method are illustrated by sensitive analysis and comparative analysis.     

Synchronous quality function deployment (QFD) over world wide web

Quality function deployment (QFD) is one of the formal techniques for effective product development. Its main purpose is to listen to the voice of the customer and deploy it down the stream of product development with minimum loss or distortion. It achieves this purpose by using a series of matrices. QFD is a team tool. However, most of computerized QFD systems are standalone and therefore offer limited support for teamwork. This paper proposes to employ the world wide web (WWW, web) technology to provide QFD services on the Internet/Intranets. The synchronized collaboration between team members distributed geographically and over time is particularly emphasized in this development. The resulting web-based QFD system requires no installation or maintenance on the client side but offers remote and simultaneous accesses and therefore supports better teamwork.     

基于Pythagorean模糊语言集多属性群决策方法

为了解决直觉语言集不能够处理隶属于与非隶属于语言值的程度之和大于1的情况,提出了Pythagorean模糊语言集。针对Pythagorean模糊语言信息的集成问题,定义了Pythagorean模糊语言数的运算法则及其得分函数、精确函数,提出了Pythagorean模糊语言加权平均（PFLWA）算子、Pythagorean模糊语言有序加权平均（PFLOWA）算子、Pythagorean模糊语言混合平均（PFLHA）算子,并讨论了相应的性质。然后基于组合权重的PFLWA算子与拓展的TOPSIS,提出了两种多属性群决策方法。最后通过实例验证了该方法的有效性。     

A fuzzy group quality function deployment model for e-CRM framework assessment in agile manufacturing

The rapid growth of the Internet and the expansion of electronic commerce applications in manufacturing have given rise to electronic customer relationship management (e-CRM) which enhances the overall customer satisfaction. However, when confronted by the range of e-CRM methods, manufacturing companies struggle to identify the one most appropriate to their needs. This paper presents a novel structured approach to evaluate and select the best agile e-CRM framework in a rapidly changing manufacturing environment. The e-CRM frameworks are evaluated with respect to their customer and financial oriented features to achieve manufacturing agility. Initially, the e-CRM frameworks are prioritized according to their financial oriented characteristics using a fuzzy group real options analysis (ROA) model. Next, the e-CRM frameworks are ranked according to their customer oriented characteristics using a hybrid fuzzy group permutation and a four-phase fuzzy quality function deployment (QFD) model with respect to three main perspectives of agile manufacturing (i.e., strategic, operational and functional agilities). Finally, the best agile e-CRM framework is selected using a technique for order preference by similarity to the ideal solution (TOPSIS) model. We also present a case study to demonstrate the applicability of the proposed approach and exhibit the efficacy of the procedures and algorithms.     

Consensus reaching process for fuzzy behavioral TOPSIS method with probabilistic linguistic q-rung orthopair fuzzy set based on correlation measure

The paper proposes a consensus reaching process for fuzzy behavioral TOPSIS method with probabilistic linguistic q-rung orthopair fuzzy sets (PLq-ROFSs) based on correlation measure. First, the operational laws of adjusted PLq-ROFSs based on linguistic scale function (LSF) for semantics of linguistic terms are introduced, where the PLq-ROFSs have same probability space. In addition, we define the score function and accuracy function of PLq-ROFS based on the proposed operational laws to compare the PLq-ROFSs. Furthermore, we propose the probabilistic linguistic q-rung orthopair fuzzy weighted averaging (PLq-ROFWA) operator and the probabilistic linguistic q-rung orthopair fuzzy order weighted averaging (PLq-ROFOWA) operator to aggregate the linguistic decision information. Considering the inconsistency between the individual information and aggregated information in decision-making process and the demiddle of given linguistic sets tocision makers' behavioral factors, we define a new correlation measure based on LSF to develop a consensus reaching process for fuzzy behavioral TOPSIS method with PLq-ROFSs. Finally, a numerical example concerning the selection of optimal green enterprise is given to illustrate the feasibility of the proposed method and some comparative analyses with the existing methods are given to show its effectiveness. The sensitivity analysis and stability analysis of the proposed method on the ranking results are also discussed.     

Planning and design of industrial engineering education quality

A Quality Function Deployment (QFD) approach to improve industrial engineering (IE) education quality at the Middle East Technical University (METU) is presented. Major stakeholders of IE education are identified as students, faculty members and future employers of the students. Requirements of these groups from an IE graduate are determined by surveys and interviews with them. These requirements are prioritized. Main education requirements are identified to meet the stakeholders' requirements. Finally, the results and plans for future studies are given.     

基于梯形模糊隶属函数的复合语言多目标决策

对于一些复杂的决策问题, 使用比较语言比单一语言更能准确地表达专家的看法. 据此, 提出一种同时使用单一语言和比较语言的新算法. 根据上下文无关文法将比较语言表达转换为犹豫模糊语言术语集(HFLTS), 并应用有序加权算子(OWA) 计算出由梯形隶属函数表示的模糊语言术语集的模糊包络, 有效地简化了基于HFLTS 的词计算过程. 最后应用逼近理想解排序(TOPSIS) 方法进行决策.